Practical Considerations for Clinical Laboratories in Top-down Approach for Assessing the Measurement Uncertainty of Clinical Chemistry Analytes
1
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Background: The top-down (TD) approach using internal quality control (IQC) data is regarded a practical method for estimating measurement uncertainty (MU) in clinical laboratories. We estimated the MU of 14 clinical chemistry analytes using the TD approach and evaluated the effect of lot changes on the MU. Methods: MU values were estimated using subgrouping by reagent lot changes or using the data as a whole, and both methods were compared. Reagent lot change was simulated using randomly generated data, and the mean values and MU for two IQC datasets (different QC material lots) were compared using statistical methods. Results: All MU values calculated using subgrouping were lower than the total values; however, the average differences were minimal. The simulation showed that the greater the increase in the extent of the average shift, the larger the difference in MU. In IQC data comparison, the mean values and MU exhibited statistically significant differences for most analytes. The MU calculation methods gave rise to minimal differences, suggesting that IQC data in clinical laboratories show no significant shift. However, the simulation results demonstrated that notable differences in the MU can arise from significant variations in IQC results before and after a reagent lot change. Additionally, IQC material lots should be treated separately when IQC data are collected for MU estimation. Conclusions: Lot changes in IQC data are a key factor affecting MU estimation and should not be overlooked during MU estimation.
Abstract
Background: The top-down (TD) approach using internal quality control (IQC) data is regarded a practical method for estimating measurement uncertainty (MU) in clinical laboratories. We estimated the MU of 14 clinical chemistry analytes using the TD approach and evaluated the effect of lot changes on the MU. Methods: MU values were estimated using subgrouping by reagent lot changes or using the data as a whole, and both methods were compared. Reagent lot change was simulated using randomly generated data, and the mean values and MU for two IQC datasets (different QC material lots) were compared using statistical methods. Results: All MU values calculated using subgrouping were lower than the total values; however, the average differences were minimal. The simulation showed that the greater the increase in the extent of the average shift, the larger the difference in MU. In IQC data comparison, the mean values and MU exhibited statistically significant differences for most analytes. The MU calculation methods gave rise to minimal differences, suggesting that IQC data in clinical laboratories show no significant shift. However, the simulation results demonstrated that notable differences in the MU can arise from significant variations in IQC results before and after a reagent lot change. Additionally, IQC material lots should be treated separately when IQC data are collected for MU estimation. Conclusions: Lot changes in IQC data are a key factor affecting MU estimation and should not be overlooked during MU estimation.
참고문헌 (16)
- Ćelap I, "Minimum requirements for the estimation of measurement uncertainty: recommendations of the joint Working group for uncertainty of measurement of the CSMBLM and CCMB", Biochem Med(Zagreb), 27, pp.030502~ (2017)
- Infusino I, "Measurement uncertainty : friend or foe?", Clin Biochem, 57, pp.3~6 (2018)
- Braga F, "Role and responsibilities of laboratory medicine specialists in the verification of metrological traceability of in vitro medical diagnostics", J Med Biochem, 34, pp.282~287 (2015)
- Braga F, "The utility of measurement uncertainty in medical laboratories", Clin Chem Lab Med, 58, pp.1407~1413 (2020)
- BIPM, "Evaluation of measurement data — Guide to the expression of uncertainty in measurement, GUM 1995 with minor corrections", JCGM, 100~ (1995)
- CLSI, "Expression of measurement uncertainty in laboratory medicine, approved guideline" (2012), Clinical and Laboratory Standards Institute
- ISO, "Medical laboratories — Practical guidance for the estimation of measurement uncertainty", ISO, 2019
- EURACHEM, "Measurement uncertainty arising from sampling: a guide to methods and approaches", ~ (2019)
- Braga F, "Performance criteria for combined uncertainty budget in the implementation of metrological traceability", Clin Chem Lab Med, 53, pp.905~912 (2015)
- Ellis AD, "Influence of reagent lots and multiple measuring systems on estimating the coefficient of variation from quality control data; implications for uncertainty estimation and interpretation of QC results", Clin Chem Lab Med, 58, pp.1829~1835 (2020)
- Johansen MB, "A simple transformation independent method for outlier definition", Clin Chem Lab Med, 56, pp.1524~1532 (2018)
- Mishra P, "Descriptive statistics and normality tests for statistical data", Ann Card Anaesth, 22, pp.67~72 (2019)
- 김혜영, "Statistical notes for clinical researchers: assessing normal distribution (2) using skewness and kurtosis", Restorative Dentistry and Endodontics, 38(1), pp.52~54 (2013), 대한치과보존학회[DOI]
- Ceriotti F, "Deriving proper measurement uncertainty from Internal Quality Control Data : an impossible mission?", Clin Biochem, 57, pp.37~40 (2018)
- Kim SY, "Commutability of proficiency testing(PT) : status of the matrix-related bias in general clinical chemistry", Clin Chem Lab Med, 51, pp.e169~e173 (2013)
- Thompson S, "Lot-to-lot variation", Clin Biochem Rev, 39, pp.51~60 (2018)